Senior Software Engineer, Machine Learning Platform
Tasks
- Align architecture with MLOps and compliance standards
- Apply formal methods for distributed inference scalability reliability performance
- Architect ML inference infrastructure
- Automate GitHub Prow workflows with Go
- Build distributed systems for inference
- Build observability with distributed tracing and performance analytics
- Detect model drift and monitor performance
- Develop ML inference services in Bazel monorepos
- Ensure low latency high throughput inference
- Implement hermetic build and secure CI CD pipelines
- Integrate feature stores for low latency delivery
- Lead design of distributed model serving
- Mentor engineers and standardize ML platform practices
- Optimize ML algorithms for memory efficiency and runtime speed
- Provision scalable reproducible cloud agnostic environments with Pulumi
Perks/Benefits
- Dental insurance
- Employee discounts
- Matching 401k
- Medical insurance
- Paid time off
- Vision insurance
- Wellness program
Skills/Tech-stack
Bazel | CD pipelines | CI/CD | CI/CD pipelines | CNN | Computational Theory | Computer Vision | Dependency Injection | Distributed tracing | Drift Detection | Feature Store | Formal Methods | GDPR | GDRP | GitHub | Go | Golang | Guice | Hermetic builds | High Throughput | Java | Low Latency | MLOps | Machine Learning | Model Drift | Model Drift Detection | Model Serving | Multimodal Models | Multithreading | Object Detection | Observability | Performance Analytics | Prow | Pulumi | Reactive Programming | SOC2 | Scala | Secure CI/CD | Secure CI/CD pipelines | Segmentation
Education
Regions
Countries
States
Cities
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